ReTracing: An Archaeological Approach Through Body, Machine, and Generative Systems

• URL: http://arxiv.org/abs/2602.11242v1
• Date: Wed, 11 Feb 2026 17:29:18 GMT
• Title: ReTracing: An Archaeological Approach Through Body, Machine, and Generative Systems
• Authors: Yitong Wang, Yue Yao,
• Abstract summary: ReTracing is a multi-agent embodied performance art that adopts an archaeological approach to examine how artificial intelligence shapes, constrains, and produces bodily movement.<n>We use large language models (LLMs) to generate paired prompts "what to do" and "what not to do" for each excerpt.<n>A diffusion-based text-to-video model transforms these prompts into choreographic guides for a human performer and motor commands for a quadruped robot.
• Score: 24.855576352876984
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present ReTracing, a multi-agent embodied performance art that adopts an archaeological approach to examine how artificial intelligence shapes, constrains, and produces bodily movement. Drawing from science-fiction novels, the project extracts sentences that describe human-machine interaction. We use large language models (LLMs) to generate paired prompts "what to do" and "what not to do" for each excerpt. A diffusion-based text-to-video model transforms these prompts into choreographic guides for a human performer and motor commands for a quadruped robot. Both agents enact the actions on a mirrored floor, captured by multi-camera motion tracking and reconstructed into 3D point clouds and motion trails, forming a digital archive of motion traces. Through this process, ReTracing serves as a novel approach to reveal how generative systems encode socio-cultural biases through choreographed movements. Through an immersive interplay of AI, human, and robot, ReTracing confronts a critical question of our time: What does it mean to be human among AIs that also move, think, and leave traces behind?

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